Self-organizing map clustering based on continuous multiresolution entropy

H.M. Torres, J.A. Gurlekian, H.L. Rufiner and M.E. Torres

Physica A: Statistical Mechanics and its Applications, 2006, vol. 361, issue 1, 337-354

Abstract: The detection of changes in the parameter values of a nonlinear dynamic system is a branch of study with multiple applications. In this paper, we explore a variant of an automatic detector and clustering of slight parameter variations in nonlinear dynamic systems proposed by Torres et al. [Automatic detection of slight changes in nonlinear dynamical systems using multiresolution entropy tools, Int. J. Bifurc. Chaos 11(4) (2001) 967–981]. The new method takes the advantages of the continuous multiresolution entropy to localize slight changes in the parameters, and uses self-organizing maps to quantify and cluster these changes. We discuss the performance of this method while applied to automatic segmentation of natural and synthetic diphthongs in the presence of additive noise. Our results show the potentiality of the proposed method.

Keywords: Wavelet transform; Continuous multiresolution entropy; Self-organizing maps; Nonlinear systems; Speech segmentation (search for similar items in EconPapers)
Date: 2006
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:361:y:2006:i:1:p:337-354

DOI: 10.1016/j.physa.2005.05.073

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